G. P. Richardson July 2006 1 Rockefeller College of Public Affairs and Policy University at Albany...

G. P. RichardsonJuly 2006

1

Rockefeller College of Public Affairs and PolicyRockefeller College of Public Affairs and PolicyUniversity at AlbanyUniversity at Albany

Dynamic Complexity50th Annual Meeting of the

International Society for the Systems Sciences

George P. Richardson

Rockefeller College of Public Affairs and Policy

University at Albany, SUNY


2


Decisions

Real World

Information Feedback

Strategy, Structure, Decision Rules

Mental Models

Virtual World

SelectedMissingDelayedBiased

Ambiguous

ImplementationGame playingInconsistency

Short term

Unknown structureDynamic complexity

Time DelaysImpossible experiments

MisperceptionsUnscientific

BiasesDefensiveness

Known structureVariable Complexity

Controlled Experiments

Learning in and about Complex Systems

Sterman (1994)

Inability to infer dynamics from mental models


3


Dynamic Complexity arises because systems are…

• Changing over time• Tightly coupled• Governed by feedback• Nonlinear: changing

dominant structure• History-dependent

• Self-organizing• Adaptive• Counterintuitive• Policy resistant• Characterized by

tradeoffs


4


System Dynamics Contributions

• Thinking dynamically• Move from events and decisions to

patterns of continuous behavior over time and policy structure

• Thinking in circular causal / feedback patterns • Self-reinforcing and self-balancing

processes

• Compensating feedback structures and policy resistance

• Communicating complex nonlinear system structure

• Thinking in stocks and flows• Accumulations are the resources

and the pressures on policy

• Policies influence flows

• Modeling and simulation• Accumulating (and remembering)

complexity

• Rigorous (daunting) model evaluation processes

• Controlled experiments

• Reflection


5


The system dynamics modeling process

SystemConceptualization

ModelFormulation

Representation ofModel Structure

Comparison andReconcilation

Perceptions ofSystem Structure

Empirical andInferred Time

Series

Comparison andReconciliation.

Deduction OfModel Behavior

Adapted from Saeed 1992


6


Processes focusing on system structure

EmpiricalEvidence


ModelFormulation




Mental Models,Experience,Literature

Diagramming andDescription Tools


7


Processes focusing on system behavior

EmpiricalEvidence


ModelFormulation

Literature,Experience


Series



ComputingAids


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Two kinds of validating processes

EmpiricalEvidence


ModelFormulation




Mental Models,Experience,Literature

Literature,Experience


Series



Diagramming andDescription Tools

ComputingAids

StructureValidatingProcesses

BehaviorValidatingProcesses


9


QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Six Traditions Contributing to the Evolution of Feedback Thought•Biology: math models•Econometrics•Engineering•Social Sciences•Biology: homeostasis•Logic

Two Threads of Feedback Thought•System dynamics arises in the servomechanisms thread(the first four in this list)


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Forrester’s Hierarchy of System Structure

• Closed boundary around the system• Feedback loops as the basic structural elements within the

boundary• Level [stock] variables representing accumulations within the

feedback loops• Rate [flow] variables representing activity within the feedback

loops• Goal

• Observed condition

• Detection of discrepancy

• Action based on discrepancy


11


The Endogenous Point of View

• The closed causal boundary takes top billing• Dynamics arise from interactions within that boundary

• Systems thinking is the mental effort to uncover endogenous sources of system behavior.


12


Dynamics


13


New York City Population, 1900-2000

9000000

8000000

7000000

6000000

5000000

4000000

3000000

2000000

1000000

01900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

BronxBrooklynManhattanQueensStaten Island

9000000

8000000

7000000

6000000

5000000

4000000

3000000

2000000

1000000

01900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

BronxBrooklynManhattanQueensStaten Island


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Global Atmospheric Methane (1860-1994)

Global Atmospheric Methane

0

50

100

150

200

250

300

350

4001860

1890

1920

1950

1980

Year

Tera

gra

ms

Global Atmospheric Methane

0

50

100

150

200

250

300

350

4001860

1890

1920

1950

1980

Year

Tera

gra

ms


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Global Average Temperature (Reconstruction 1400-1980; Data 1902-1998)

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.


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Stocks and Flows


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Stocks and flows help to explain self-reported drug use data

Potentialusers

Occasionalusers

Frequentusers

Past users

Haveeverused


18


‘Challenging the clouds’ in a study of leasing in the automobile industry

“We’re not in the used car business!”

New vehicleinventory

Production Purchaseor lease

?


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Stocks and flows in new car purchase and leasing

New vehicleinventory

Production

Vehiclesbeing driven

Purchaseor lease

Scrapping

Usedinventory

Sell ortrade in

Purchaseused

Relativeattractivenessof leased cars

Trade cycle


20


Intuitive view of effect of leasing on auto sales:

Leased car pipeline

Stock

SalesStrength of the economy, price


21


Stocks and Flows in Global Warming

Capitalstock

capitalinvestment

AtmosphericCO2CO2 annual

productionBreakdown of

atmopheric CO2

Economicactivity

Global heatenergyincoming solar

heat energyoutgoing global

heat energy

Thought experiment:


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Earth Ocean and Atm heat

Earth ice

Net thawing

Earth heat radiation

Earth water Water vapor in atm

Condensation

Water in clouds

Cloud cover~

GH gas reten efct

Evaporation

Precipitation

~

Cloud reten efct

Solar heat incoming

Atm temp

Surface temp

Solar heat reaching earth

~

CO2 reten efct

Atm volumeWater vap conc

Ice cover

Aerosols in atm

Atm volume

Aerosol production

GH gases in atm

Aerosol breakdown GH gas production GH gas breakdown

Aerosol concentration

~

Aerosol albedo efct

Life of GH gases in atm

Water density

Total albedo

GH gas concentrationAtm volume

CO2 in oceans

Life of aerosols in atm

Carbon in ocean biomass

Ocean photosynthesis

Ocean biomass decay

Ocean CO2 breakdown

CO2 in atm

CO2 ocean release

CO2 ocean uptake

Carbon in earth biomassAtm CO2 breakdown

Atm CO2 production

Atm volume

CO2 atm conc

Ocean CO2 production

Earth water volume

Earth photosynthesis

Earth biomass decay

Ice thickness

Ice density

Earth area

CO2 water conc

Cloud volume

Ice volume

Ice areaCloud area

Earth area

Cloud density

Cloud thicknessWater vap reten efct

Evap factor

~

Net thawing factor

~

Ice and cloud cover

But although the stock-and-flow insight holds, global climate is of course much more complex than that.

And still much more complex than this simple global climate model, as well!


23


Feedback Thinking

“For one good deed leads to another good deed, and one transgression leads to another transgression.” (Pirke Avot)


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The Classic Cybernetic Balancing LoopGoal Perceived

gapPlannedaction to

reduce gap

Implementedaction

Intendedactions

Actual state ofthe system

Perceivedstate

Implicit,unstated goals

Changes inthe State ofthe system


25


The Cybernetic Loop with ComplicationsGoal Perceived

gapPlannedaction to

reduce gap

Implementedaction

Intendedactions


Perceivedstate

Autonomouschanges in the state

of the system




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gapPlannedaction to

reduce gap

Implementedaction

Intendedactions


Perceivedstate

Unintendedactions


of the system




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gapPlannedaction to

reduce gap

Implementedaction

Intendedactions


Perceivedstate

Unintendedactions


of the system

Ramifyingeffects




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A Classic Reinforcing Loop(Myrdal 1944, Merton 1948)

Prejudice against the minority group

Majority’s perception of the inferiority of the

minority

Economic and educational

discrimination against the minority

Achievements of the minority group

(R)


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Structure and Dynamics of Terrorist Cells

Recruiting terrorists

Terrorist group

Losing terrorists

Terrorist actions

Efforts to suppress terrorists

Terrorist zeal

Peripheral support for terrorists

Terrorist funding

Terrorist martyrs to the cause

(R)

(B)(R)

(R)

(R)

(B)

(R)

(R)

Interfering with terrorist funding

(B)

(B)


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Teamwork and Communication are self-reinforcing

Insights about building teamwork in a public schoolInsights about building teamwork in a public school

Quality ofcommunication

Trust

Risktaking

Teamwork

+

+

+

(+)


within teams

+

+

Resistance toteamwork

-


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Isolation of teams and punishing risk-taking inhibit the growth of trust


Trust

Risktaking

Teamwork

+

+

+

Quality ofcommunicationbetween teams

+

(+)

Individualexperiments

Positiveresponses toexperiments

+?

+

(+/-)


within teams

+

+ -(-)


-


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But longterm experience with teamwork can build communication


Trust

Risktaking

Teamwork

+

+

+

Cumulativeexperience with

teamwork

+


++

(+)



+?

+

(+/-)


within teams

+

+ -

+

(-)

(+)

Teameffectiveness


-

-

+ +


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Risk taking can enhance effectiveness, which can build trust


Trust

Risktaking

Teamwork

+

+

+


teamwork

+


++

(+)



+?

+

(+/-)


within teams

+

+ -

+

(-)

(+)

Teameffectiveness


-

-

+

Personal learning+

Average personaleffectiveness+

+

+


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A team-player culture is self-reinforcing: an opportunity or a trap


Trust

Risktaking

Teamwork

+

+

+


teamwork

+


++

(+)



+?

+

(+/-)


within teams

+

+ -

+

(-)

(+)

Teameffectiveness


-

-

+

Personal learning+


+

+

Attractivenessof the org toteam players+

Fraction ofstaff who areteam players

+

+


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Likely leverage points


Trust

Risktaking

Teamwork

+

+

+


teamwork

+


++

(+)



+?

+

(+/-)

Quality ofcommunicationwithin teams

+

+ -

+

(-)

(+)

Teameffectiveness


-

-

+

Extent ofLearning

Organizationcharacteristics

present

Admteaching

role

+

+

Personal learning+


+Understanding

stages ofcommunity

building

+

+

Attractivenessof the org toteam players+

Fraction ofstaff who areteam players

+

+

Dialoguetraining

+

+


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The Problem: 1996 U.S. welfare reform• Since 1930, a guarantee of lifetime Federal support• 1996 legislation ended that:

• Temporary Assistance for Needy Families - TANF

• At most five years of Federal support in one’s lifetime

• The clock started for everyone on TANF in 1997• People began timing out in 2002• Financial burden will begin shifting to the states and

counties• A series of facilitated group modeling efforts in three New

York State counties tried to help counties cope. Where are the leverage points?


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Three Policy Mixes• Base run (for comparison)

• Flat unemployment rate

• Historical client behaviors

• Investments in the “Middle”• Additional services to TANF families

• Increased TANF assessment & monitoring

• Safety net assessment & job services

• Investments on the “Edges” • Prevention

• Child support enforcement

• Self-sufficiency promotion


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Investing in the “Middle”


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Investing on the “Edges”


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Base, “Edges,” and “Middle” Compared:Populations on the Welfare Rolls

“Edges” looks better.


43


Total Job-Finding Flows from TANF

“Middle” looks better.


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Program Expenditures

“Edges” looks worse, then better.


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Populations in the Welfare System

“Middle” looks worse than “Base”! “Edges” looks much better.


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Total Recidivism Flows (back to TANF)

The hint for understanding the puzzling dynamics: recidivism.


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A Stock-and-Flow Archetype at Work Here

Families onTANF

Post TANFemployedJob finding

rate

Recidivism

Load on employmentsupport capacity

Probability ofrecidivism

+

+

Time to findfirst job

Load on TANFsupport capacity

To mainstreamemployment

-

Enter TANF

(R) (R)

(R)


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6,000

4,500

3,000

1,500

0

0 6 12 18 24 30 36 42 48 54 60Time (Month)

Families on TANF : archetype base familiesPost TANF employed : archetype base familiesTotal families at risk : archetype base families

Behavior of the Archetype in response to increased TANF support capacity

Total families at risk

Post-TANF employed

Families on TANF


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The Behavior of the Archetype

• Families on TANF initially declines, as more support hastens job finding.

• Post-TANF families employed initially increases, just as policy makers would predict.

• Eventually (it takes a year and a half to begin to see it), …• Families on TANF rises higher to a new high,

• Post-TANF Employed declines to a new low,

• And Total Families at Risk rises!

• …All because of increased TANF support capacity!


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Enter TANF Families onTANF+

-

Recidivism

+

Outflow from postTANF employ

Post TANFemployed

Time in postTANF employ

Job findingrate +

-


-




TANF supportcapacity


Post TANF employmentsupport capacity

Why? • Increasing TANF support• Speeds job finding, • Swamping downstream Post-TANF jobs and support


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Misattribution?• Desirable rise in Post-TANF employed continues for

almost a year and half after the intervention• Families on TANF falls below initial for over a year after

increasing TANF support capacity• Very hard (impossible?) to see that the rise in Total

Families at Risk is attributable solely to the improvement in TANF support capacity

• Dynamics almost certainly to be blamed on a weakening economy, a rise in client pathologies, or other exogenous factors


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-

Recidivism

+


Post TANFemployed


Job findingrate +

-


-







A Loop View of the Archetype in Detail

Suppose TANF support capacity increases…


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120

B: Employed load controls recidivism

4,000

3,000

2,000

1,000

0

0 30 60 90Time (Month)


-

Recidivism

+


Post TANFemployed


Job findingrate +

-


-







White bar (left) is the time slice of interest

Red arrows (below) are the dominant influences


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120


4,000

3,000

2,000

1,000

0



-

Recidivism

+


Post TANFemployed


Job findingrate +

-


-








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120


4,000

3,000

2,000

1,000

0



-

Recidivism

+


Post TANFemployed


Job findingrate +

-


-








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120


4,000

3,000

2,000

1,000

0



-

Recidivism

+


Post TANFemployed


Job findingrate +

-


-








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120


4,000

3,000

2,000

1,000

0



-

Recidivism

+


Post TANFemployed


Job findingrate +

-


-







White bar (left) is the time slice of interest

Red arrows (below) are the dominant influences


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120


4,000

3,000

2,000

1,000

0



-

Recidivism

+


Post TANFemployed


Job findingrate +

-


-








59


120


4,000

3,000

2,000

1,000

0



-

Recidivism

+


Post TANFemployed


Job findingrate +

-


-








60


120


4,000

3,000

2,000

1,000

0



-

Recidivism

+


Post TANFemployed


Job findingrate +

-


-








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120


4,000

3,000

2,000

1,000

0



-

Recidivism

+


Post TANFemployed


Job findingrate +

-


-








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120


4,000

3,000

2,000

1,000

0



-

Recidivism

+


Post TANFemployed


Job findingrate +

-


-







Dynamic complexity even in a structure this aggregate and tiny!


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System Dynamics and Dynamic Complexity

• Thinking dynamically moves us beyond separate events and decisions, toward understanding.

• Feedback thinking extends traditional causal thinking.• It improves (makes more realistic) how we think about

the world and how we think about changing it.

• The endogenous point of view is empowering.

G. P. Richardson July 2006 1 Rockefeller College of Public Affairs and Policy University at Albany...

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